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responsibility, and a deep commitment to genuine care and respect for our community. Find out more about our vision for a truly inclusive workplace in our Diversity, Inclusion and Belonging Framework . Flexible
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degree in mathematics, strongly encouraged to apply. Experience and demonstratable knowledge in deep learning and one or more of the following: transformer networks, implicit neural functions, graph neural
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About the Opportunity About the Opportunity Northeastern University Pharmaceutical Industry Fellowships Program is a two-year experiential program designed to advance lifelong learning and the
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-depth study of existing approaches to AI-based water leak detection and prediction, including classical methods and modern deep learning techniques. 2) Requirements survey Identification of the technical
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. Are you a Computer Scientist looking to apply your expertise to real-world weather forecasting challenges in Africa? Machine-learning has the potential to revolutionise weather prediction for and in Africa
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PhD in Computer Science, Engineering or other Machine Learning-related field. • Programming experience in python, C++ or other relevant language and experience in deep neural networks • Strong
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About the Opportunity About the Opportunity Northeastern University Pharmaceutical Industry Fellowships Program is a two-year experiential program designed to advance lifelong learning and the
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or testing deep learning models for genomics, exploring new techniques related to spatial simulations, or other topics discussed with the PI. Core job duties include: (1) Designing, implementing, and
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Engineering, Automation, Mechanical Engineering, Control Engineering, Mechatronics, Computer Science, AI, etc. Strong background in autonomous driving, deep learning, interaction modelling, prediction, robotics
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 23 days ago
deep learning theory and practice. Applicants with expertise in probabilistic modelling, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine